Checklist

LangGraph human-in-the-loop checklist

Before a LangGraph agent calls a risky tool, add an approval gate that can pause, notify a human, record the decision, and resume only the reviewed action.

This page is a short checklist. The AI Agent Approval Policy Pack includes a fuller LangGraph checklist, JSON policies, and reviewer runbooks.

1. Classify risky tool calls

2. Create a durable approval request

Store the proposed action, target resource, arguments, policy result, agent confidence, reviewer role, timeout, and idempotency key. Do not rely on a transient chat message as the only approval record.

3. Pause before the side effect

The graph should pause before calling the risky tool. If the approval request cannot be created or delivered, fail closed and return a blocked result to the agent.

4. Resume only the approved action

When a reviewer approves, compare the current tool arguments with the reviewed request. If the resource, parameters, policy version, or approval window changed, require a fresh review.

5. Keep an audit trail

Downloadable templates

Ship the approval gate faster.

Get ready-to-edit policies, LangGraph checklist details, OpenClaw/Codex dispatch checks, Feishu/Lark guidance, and production readiness notes.